Offshore wind energy has experienced remarkable growth in terms of installed capacity and investment in the past two decades. The current trend shows that offshore wind projects are moving further from shore and in deeper waters to increase efficiency and limit conflicts with other sea users. However, offshore wind projects are subject to a number of risks including but not limited to policy risks, resource unavailability (in particular vessels), weather risks, and grid inaccessibility. The occurrence of such risks can increase the cost of projects. Therefore in order to minimise the effect of these risks, decision makers may wish to develop risk mitigation actions.In this seminar an overview of these risks are presented and a set of mitigation actions are introduced. According to the risk tolerance of the decision maker, cost targets are defined, based on which the optimal set of risk mitigation strategies can be determined. This research arises from the FP7 project, Leanwind, supported by the European Union. Leanwind is a consortium of 31 industry and academic partners, which aims to reduce the cost of offshore wind energy through employing improved turbine and foundation technologies, efficient logistics, and novel business models.

Method

A mixed-model methodology for the optimal choice of a set of risk mitigation measures is proposed based on a set of identified risks. The methodology combines the techniques of Monte Carlo simulation, and decision analytics in order to generate risk mitigation strategies corresponding to the problem owner(s) goals and preferences with respect to a set of underlying criteria.

Results

In this research a set of risks, potential mitigation actions, and a set of mitigation strategies based on the decisions maker's risk tolerance are identified. The proposed method will help the decision makers in the offshore wind sector to choose the most optimal risk mitigation strategy (the one that yields the least cost) for different confidence levels (e.g.75%, 90%, 95%). Different confidence levels accommodate the difference in decision makers' risk tolerance.

Conclusions

Given the high cost and risk of offshore wind projects, the selection of effective risk management strategies is critical for the sustainability of the industry. This work introduces a method for offshore wind project risk mitigation that incorporates decision maker's targets and risk tolerance. Uncertainties in the offshore wind industry are recognized and effective ways to incorporate them in the decision making process have been introduced. It is envisaged that using such techniques will help decision makers to make more informed, and optimal choices resulting in a more effective project risk management.

Objectives

Offshore wind projects are considered more complex compared to the established onshore wind projects. The complexity of these projects is accompanied by increased risk which requires more sophisticated risk mitigation strategies. From a practical standpoint, this research aims to help decision makers in recognizing various risks for offshore wind projects, identify a set of mitigation actions, and select the optimal strategy based on the risk tolerance for different confidence levels and thus better understand the value of their project under given different risk factors.